R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(86.86,86.79,82.52,86.87,81.62,82.66,89.87,92.04,79.74,77.75,79.12,76.37,75.01,77.6,77.81,81.7,76.47,74.72,84.43,86.72,70.99,75.43,74.14,73.3,71.97,69.27,74.13,76.4,72.26,72.1,87.82,91.62,82.69,85.76,86.87,93.09,83.73,84.49,87.37,89.13,83.2,83.77,93.68,93.09,88.59,87.88,87.89,89.38,89.13,89.58,90.22,91.44,91.04,92.1,97.54,99.12,100,99.68,100.08,99.9,99.63,99.45,99.63,99.46,96.91,97.65,102.1,103.57,104.59,104.79,101.31,104.8,104.56,104.15,102.73,101.86,101.9,102.33,105.71,106.1,102.81,103.23,102.35,104.11)
> par1 = '12'
> par1 <- '12'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P. (2012), Standard Deviation-Mean Plot (v1.0.6) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_smp.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 84
> (np <- floor(n / par1))
[1] 7
> arr <- array(NA,dim=c(par1,np))
> j <- 0
> k <- 1
> for (i in 1:(np*par1))
+ {
+ j = j + 1
+ arr[j,k] <- x[i]
+ if (j == par1) {
+ j = 0
+ k=k+1
+ }
+ }
> arr
       [,1]  [,2]  [,3]  [,4]   [,5]   [,6]   [,7]
 [1,] 86.86 75.01 71.97 83.73  89.13  99.63 104.56
 [2,] 86.79 77.60 69.27 84.49  89.58  99.45 104.15
 [3,] 82.52 77.81 74.13 87.37  90.22  99.63 102.73
 [4,] 86.87 81.70 76.40 89.13  91.44  99.46 101.86
 [5,] 81.62 76.47 72.26 83.20  91.04  96.91 101.90
 [6,] 82.66 74.72 72.10 83.77  92.10  97.65 102.33
 [7,] 89.87 84.43 87.82 93.68  97.54 102.10 105.71
 [8,] 92.04 86.72 91.62 93.09  99.12 103.57 106.10
 [9,] 79.74 70.99 82.69 88.59 100.00 104.59 102.81
[10,] 77.75 75.43 85.76 87.88  99.68 104.79 103.23
[11,] 79.12 74.14 86.87 87.89 100.08 101.31 102.35
[12,] 76.37 73.30 93.09 89.38  99.90 104.80 104.11
> arr.mean <- array(NA,dim=np)
> arr.sd <- array(NA,dim=np)
> arr.range <- array(NA,dim=np)
> for (j in 1:np)
+ {
+ arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
+ arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
+ arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
+ }
> arr.mean
[1]  83.51750  77.36000  80.33167  87.68333  94.98583 101.15750 103.48667
> arr.sd
[1] 4.948804 4.681960 8.544875 3.469423 4.705792 2.792588 1.434734
> arr.range
[1] 15.67 15.73 23.82 10.48 10.95  7.89  4.24
> (lm1 <- lm(arr.sd~arr.mean))

Call:
lm(formula = arr.sd ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
    18.7968      -0.1607  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))

Call:
lm(formula = log(arr.sd) ~ log(arr.mean))

Coefficients:
  (Intercept)  log(arr.mean)  
       18.725         -3.867  

> (lm2 <- lm(arr.range~arr.mean))

Call:
lm(formula = arr.range ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
    60.5138      -0.5327  

> postscript(file="/var/fisher/rcomp/tmp/1hgpt1386100342.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/2lz3r1386100342.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
> dev.off()
null device 
          1 
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Section',header=TRUE)
> a<-table.element(a,'Mean',header=TRUE)
> a<-table.element(a,'Standard Deviation',header=TRUE)
> a<-table.element(a,'Range',header=TRUE)
> a<-table.row.end(a)
> for (j in 1:np) {
+ a<-table.row.start(a)
+ a<-table.element(a,j,header=TRUE)
+ a<-table.element(a,arr.mean[j])
+ a<-table.element(a,arr.sd[j] )
+ a<-table.element(a,arr.range[j] )
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/3kcte1386100342.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/4jh0d1386100342.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Lambda',header=TRUE)
> a<-table.element(a,1-lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/5xv0z1386100342.tab") 
> 
> try(system("convert tmp/1hgpt1386100342.ps tmp/1hgpt1386100342.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lz3r1386100342.ps tmp/2lz3r1386100342.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.996   0.550   2.530